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Overcoming the limitations of patch-based learning to detect cancer in
  whole slide images

Overcoming the limitations of patch-based learning to detect cancer in whole slide images

1 December 2020
Ozan Ciga
Tony Xu
S. Nofech-Mozes
S. Noy
F. Lu
Anne L. Martel
ArXivPDFHTML

Papers citing "Overcoming the limitations of patch-based learning to detect cancer in whole slide images"

12 / 12 papers shown
Title
From Pixels to Histopathology: A Graph-Based Framework for Interpretable Whole Slide Image Analysis
From Pixels to Histopathology: A Graph-Based Framework for Interpretable Whole Slide Image Analysis
Alexander Weers
Alexander H. Berger
Laurin Lux
Peter Schüffler
Daniel Rueckert
Johannes C. Paetzold
42
0
0
14 Mar 2025
Distilling High Diagnostic Value Patches for Whole Slide Image
  Classification Using Attention Mechanism
Distilling High Diagnostic Value Patches for Whole Slide Image Classification Using Attention Mechanism
Tianhang Nan
Hao Quan
Yong Ding
Xingyu Li
Kai Yang
Xiaoyu Cui
17
0
0
29 Jul 2024
URCDM: Ultra-Resolution Image Synthesis in Histopathology
URCDM: Ultra-Resolution Image Synthesis in Histopathology
Sarah Cechnicka
James G. C. Ball
Matthew Baugh
Hadrien Reynaud
Naomi Simmonds
A. Smith
Catherine Horsfield
C. Roufosse
Bernhard Kainz
MedIm
26
0
0
18 Jul 2024
PathAlign: A vision-language model for whole slide images in
  histopathology
PathAlign: A vision-language model for whole slide images in histopathology
Faruk Ahmed
Andrew Sellergren
Lin Yang
Shawn Xu
Boris Babenko
...
S. Shetty
Daniel Golden
Yun-hui Liu
David F. Steiner
Ellery Wulczyn
LM&MA
VLM
36
14
0
27 Jun 2024
STimage-1K4M: A histopathology image-gene expression dataset for spatial
  transcriptomics
STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics
Jiawen Chen
Muqing Zhou
Wenrong Wu
Jinwei Zhang
Yun Li
Didong Li
24
6
0
10 Jun 2024
Seeing the random forest through the decision trees. Supporting learning
  health systems from histopathology with machine learning models: Challenges
  and opportunities
Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities
Ricardo Gonzalez
Ashirbani Saha
Clinton J.V. Campbell
Peyman Nejat
Cynthia Lokker
Andrew P. Norgan
33
12
0
06 Dec 2023
Gravity Network for end-to-end small lesion detection
Gravity Network for end-to-end small lesion detection
Ciro Russo
Alessandro Bria
Claudio Marrocco
MedIm
24
0
0
22 Sep 2023
Probabilistic Attention based on Gaussian Processes for Deep Multiple
  Instance Learning
Probabilistic Attention based on Gaussian Processes for Deep Multiple Instance Learning
Arne Schmidt
Pablo Morales-Álvarez
Rafael Molina
16
13
0
08 Feb 2023
Computer-Aided Cancer Diagnosis via Machine Learning and Deep Learning:
  A comparative review
Computer-Aided Cancer Diagnosis via Machine Learning and Deep Learning: A comparative review
Solene Bechelli
11
2
0
19 Oct 2022
Influence of uncertainty estimation techniques on false-positive
  reduction in liver lesion detection
Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection
Ishaan Bhat
J. Pluim
M. Viergever
Hugo J. Kuijf
MedIm
19
4
0
22 Jun 2022
Improving Self-supervised Learning with Hardness-aware Dynamic
  Curriculum Learning: An Application to Digital Pathology
Improving Self-supervised Learning with Hardness-aware Dynamic Curriculum Learning: An Application to Digital Pathology
C. Srinidhi
Anne L. Martel
34
22
0
16 Aug 2021
Self supervised contrastive learning for digital histopathology
Self supervised contrastive learning for digital histopathology
Ozan Ciga
Tony Xu
Anne L. Martel
SSL
103
305
0
27 Nov 2020
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